In this paper we demonstrate that standard methods of asymptotic inference will break down in a binary choice duration model in a time series setting. This comes about because the dependent variable has a degenerate limit distribution, which makes the asymptotic variance-covariance matrix singular. This result has implications for discrete choice duration panel data models under large N and T a...

We present a general framework to model strategic aspects and stable and fair resource allocations in networks via variants and generalizations of path coalitional games. In these games, a coalition of edges or vertices is successful if it can enable an s-t path. We present polynomial-time algorithms to compute and verify least core payoffs of cost-based generalizations of path coalitional game...

accurate groundwater level modeling and forecasting contribute to civil projects, land use, citys planning and water resources management. combined wavelet-artificial neural network (wann) model has been widely used in recent years to forecast hydrological and hydrogeological phenomena. this study investigates the sensitivity of the pre-processing to the wavelet type and decomposition level in ...

In this paper we introduce a modification of the real discrete Fourier transform and its inverse transform to filter noise and perform reduction on the data whilst preserving the trend of global moving of time series. The transformed data is still in the same time domain as the original data, and can therefore be directly used by any other mining algorithms. We also present a classification alg...

There are many techniques developed for tackling time series and most of them consider every part of a sequence equally. In many applications, however, recent data can often be much more interesting and significant than old data. This paper defines new recent-biased measures for distance and energy, and proposes a recent-biased technique based on DWT for time series in which more recent data ar...

In 1979 Frankl conjectured that in a finite non-trivial union-closed collection of sets there has to be an element that belongs to at least half the sets. We show that this is equivalent to the conjecture that in a finite non-trivial graph there are two adjacent vertices each belonging to at most half of the maximal stable sets. In this graph formulation other special cases become natural. The ...

With time series data, there is often the issue of finding accurate approximations for the variance of such quantities as the sample autocovariance function or spectral estimate. Smith and Field (1993) proposed a variance estimate motivated by resampling in the frequency domain. In this paper we present some results on the cumulants of this and other frequency domain estimates obtained via symb...

Though binary choice and multiple choice models have been a popular tool of microeconometrics for many years, there are macroeconomic time series that are connected with discrete decisions of authorities. Therefore it is very important to develop an appropriate tool for statistical inference for such macroeconomic time series. Macroeconomic continuous time series may be stationary as well as in...

Brain Electroencephalography (EEG) classification is widely applied to analyze cerebral diseases in recent years. Unfortunately, invalid/noisy EEGs degrade the diagnosis performance and most previously developed methods ignore the necessity of EEG selection for classification. To this end, this paper proposes a novel maximum weight clique-based EEG selection approach, named mwcEEGs, to map EEG ...

We extract the frequency content of a noisy signal by use of Discrete Fourier Transform. Our analysis overcomes the limitations imposed by incommensurate lattices. After computing the deterministic component, we show the relevance of the method in removing spurious autocorrelations from the signal residuals. Results are presented for a temperature time series.